code: def _fuse_preprocess(self, evaluator: Evaluator) -> None:
      self.register_output_backward_hook()
      module_name_param_dict = self.patch_optimizer_param_group()
      if len(module_name_param_dict) > 0:
          evaluator.patch_optim_param_group(module_name_param_dict)
      self.register_trigger(evaluator)
  
imports: from __future__ import annotations
  import logging
  from typing import List, Dict, Union, overload
  import torch
  import torch.nn
  from torch import Tensor
  from nni.common.version import torch_version_is_2
  from ..base.compressor import Compressor, Quantizer
  from ..base.wrapper import ModuleWrapper
  from ..utils import Evaluator, _EVALUATOR_DOCSTRING
  from ..base.target_space import TargetType, QuantizationTargetSpace
label_desc: Use image node_id 14 for calling the DoReFaQuantizer obj's underlying member method code with example usage: obj._fuse_preprocess(evaluator) without return types